In this paper, a novel approach to control a single generator, connected to an infinite bus, is presented. Modifying published results for nonlinear identification using recurrent neural networks, a block controllable neural identifier is proposed, based on this neural model a control law is derived, which combines sliding modes and block control. The neural identifier and the proposed control ...

This paper discusses the systematic design of an adaptive feedback linearizing neurocontroller for a high-order model of the synchronous machine/infinite bus power system. The power system is first modelled as an input-output nonlinear discrete-time system approximated by two neural networks. The approach allows a simple linear pole-placement controller (which is itself not a neural network) to...

Power system transient stability analysis requires an appropriate integration time step to avoid numerical instability as well as to reduce computational demands. For fast system dynamics, which vary more rapidly than what the time step covers, a fraction of the time step, called a subinterval, is used. However, the optimal value of this subinterval is not easily determined because the analysis...

This paper presents an alternate approach for designing power system stabilizers (PSS) based on variable structure control to enhance small signal stability of Single Machine Infinite-Bus Power System (SMIB). The state feedback gains and switching surface have been tuned using Global Optimization (multistart clustering GO) for an Eigen value based performance index. The robustness of the propos...

In this paper, the goal is the improvement of transient condition in a single machine system with designing of the nonlinear controllers for static Synchronous Compensator (STATCOM). By obtaining the Lyapunov function in presence of compensator in the system, some controllers are designed for it which by satisfying the Lyapunov stability criteria will increase the margin of transient stability ...